Open-Source Research Infrastructure
Building the foundation for reproducible, scalable computational research. Trusted by leading labs, PhD scholars, and AI startups worldwide.
Our Projects
Open-source tools and frameworks powering the next generation of computational research.
PyLabFlow
ActiveCore framework for component-based experiment management. Enables reproducible, queryable computational research.
ExperTrack
BetaReal-time experiment tracking dashboard with lineage visualization and structural query interface.
ComponentLib
ActiveCommunity-contributed library of pre-built research components for common ML architectures and workflows.
ConfigSchema
StableDeclarative configuration system for defining experiment parameters with validation and versioning.
Trusted by Leading Researchers
Hear from PhD scholars, AI startups, and research labs using ExperQuick infrastructure.
"PyLabFlow transformed how our lab manages experiments. We went from spreadsheets and scattered notebooks to a fully queryable experiment database in weeks."
"As a PhD student running thousands of experiments, ExperQuick saved me months of work. I can now reproduce any result from my thesis instantly."
"Our startup runs 10,000+ experiments weekly. PyLabFlow's component system lets us iterate on model architectures 5x faster than before."
"The structural query feature is a game-changer. We can answer questions like 'which attention mechanism works best with our data augmentation?' in seconds."
"Reproducibility used to be our biggest pain point. Now every experiment is automatically versioned and traceable. Our review process is 3x faster."
"We integrated PyLabFlow into our drug discovery pipeline. The modular component system maps perfectly to our molecular screening workflows."
Join Our Growing Community
Whether you're a PhD researcher, AI startup, or research lab — become part of the movement transforming computational research.